Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements.

Vocal production learning ("vocal learning") is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.

The contribution of historical processes to contemporary extinction risk in placental mammals.

Species persistence can be influenced by the amount, type, and distribution of diversity across the genome, suggesting a potential relationship between historical demography and resilience. In this study, we surveyed genetic variation across single genomes of 240 mammals that compose the Zoonomia alignment to evaluate how historical effective population size (Ne) affects heterozygosity and deleterious genetic load and how these factors may contribute to extinction risk. We find that species with smaller historical Ne carry a proportionally larger burden of deleterious alleles owing to long-term accumulation and fixation of genetic load and have a higher risk of extinction. This suggests that historical demography can inform contemporary resilience. Models that included genomic data were predictive of species' conservation status, suggesting that, in the absence of adequate census or ecological data, genomic information may provide an initial risk assessment.

Evolutionary constraint and innovation across hundreds of placental mammals.

Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (~10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth's vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.

Leveraging base-pair mammalian constraint to understand genetic variation and human disease.

Thousands of genomic regions have been associated with heritable human diseases, but attempts to elucidate biological mechanisms are impeded by an inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function, agnostic to cell type or disease mechanism. Single-base phyloP scores from 240 mammals identified 3.3% of the human genome as significantly constrained and likely functional. We compared phyloP scores to genome annotation, association studies, copy-number variation, clinical genetics findings, and cancer data. Constrained positions are enriched for variants that explain common disease heritability more than other functional annotations. Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

Relating enhancer genetic variation across mammals to complex phenotypes using machine learning.

Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challenging because enhancer activity can be tissue-dependent and functionally conserved despite low sequence conservation. We developed the Tissue-Aware Conservation Inference Toolkit (TACIT) to associate candidate enhancers with species' phenotypes using predictions from machine learning models trained on specific tissues. Applying TACIT to associate motor cortex and parvalbumin-positive interneuron enhancers with neurological phenotypes revealed dozens of enhancer-phenotype associations, including brain size-associated enhancers that interact with genes implicated in microcephaly or macrocephaly. TACIT provides a foundation for identifying enhancers associated with the evolution of any convergently evolved phenotype in any large group of species with aligned genomes.

Leveraging Base Pair Mammalian Constraint to Understand Genetic Variation and Human Disease.

Although thousands of genomic regions have been associated with heritable human diseases, attempts to elucidate biological mechanisms are impeded by a general inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function that is agnostic to cell type or disease mechanism. Here, single base phyloP scores from the whole genome alignment of 240 placental mammals identified 3.5% of the human genome as significantly constrained, and likely functional. We compared these scores to large-scale genome annotation, genome-wide association studies (GWAS), copy number variation, clinical genetics findings, and cancer data sets. Evolutionarily constrained positions are enriched for variants explaining common disease heritability (more than any other functional annotation). Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

Evolution of the ancestral mammalian karyotype and syntenic regions.

Decrypting the rearrangements that drive mammalian chromosome evolution is critical to understanding the molecular bases of speciation, adaptation, and disease susceptibility. Using 8 scaffolded and 26 chromosome-scale genome assemblies representing 23/26 mammal orders, we computationally reconstructed ancestral karyotypes and syntenic relationships at 16 nodes along the mammalian phylogeny. Three different reference genomes (human, sloth, and cattle) representing phylogenetically distinct mammalian superorders were used to assess reference bias in the reconstructed ancestral karyotypes and to expand the number of clades with reconstructed genomes. The mammalian ancestor likely had 19 pairs of autosomes, with nine of the smallest chromosomes shared with the common ancestor of all amniotes (three still conserved in extant mammals), demonstrating a striking conservation of synteny for ∼320 My of vertebrate evolution. The numbers and types of chromosome rearrangements were classified for transitions between the ancestral mammalian karyotype, descendent ancestors, and extant species. For example, 94 inversions, 16 fissions, and 14 fusions that occurred over 53 My differentiated the therian from the descendent eutherian ancestor. The highest breakpoint rate was observed between the mammalian and therian ancestors (3.9 breakpoints/My). Reconstructed mammalian ancestor chromosomes were found to have distinct evolutionary histories reflected in their rates and types of rearrangements. The distributions of genes, repetitive elements, topologically associating domains, and actively transcribed regions in multispecies homologous synteny blocks and evolutionary breakpoint regions indicate that purifying selection acted over millions of years of vertebrate evolution to maintain syntenic relationships of developmentally important genes and regulatory landscapes of gene-dense chromosomes.

Ancestry-inclusive dog genomics challenges popular breed stereotypes.

Behavioral genetics in dogs has focused on modern breeds, which are isolated subgroups with distinctive physical and, purportedly, behavioral characteristics. We interrogated breed stereotypes by surveying owners of 18,385 purebred and mixed-breed dogs and genotyping 2155 dogs. Most behavioral traits are heritable [heritability (h2) > 25%], and admixture patterns in mixed-breed dogs reveal breed propensities. Breed explains just 9% of behavioral variation in individuals. Genome-wide association analyses identify 11 loci that are significantly associated with behavior, and characteristic breed behaviors exhibit genetic complexity. Behavioral loci are not unusually differentiated in breeds, but breed propensities align, albeit weakly, with ancestral function. We propose that behaviors perceived as characteristic of modern breeds derive from thousands of years of polygenic adaptation that predates breed formation, with modern breeds distinguished primarily by aesthetic traits.

Epigenomics as a paradigm to understand the nuances of phenotypes.

Quantifying the relative importance of genomic and epigenomic modulators of phenotype is a focal challenge in comparative physiology, but progress is constrained by availability of data and analytic methods. Previous studies have linked physiological features to coding DNA sequence, regulatory DNA sequence, and epigenetic state, but few have disentangled their relative contributions or unambiguously distinguished causative effects ('drivers') from correlations. Progress has been limited by several factors, including the classical approach of treating continuous and fluid phenotypes as discrete and static across time and environment, and difficulty in considering the full diversity of mechanisms that can modulate phenotype, such as gene accessibility, transcription, mRNA processing and translation. We argue that attention to phenotype nuance, progressing to association with epigenetic marks and then causal analyses of the epigenetic mechanism, will enable clearer evaluation of the evolutionary path. This would underlie an essential paradigm shift, and power the search for links between genomic and epigenomic features and physiology. Here, we review the growing knowledge base of gene-regulatory mechanisms and describe their links to phenotype, proposing strategies to address widely recognized challenges.

Broad host range of SARS-CoV-2 predicted by comparative and structural analysis of ACE2 in vertebrates.

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of COVID-19. The main receptor of SARS-CoV-2, angiotensin I converting enzyme 2 (ACE2), is now undergoing extensive scrutiny to understand the routes of transmission and sensitivity in different species. Here, we utilized a unique dataset of ACE2 sequences from 410 vertebrate species, including 252 mammals, to study the conservation of ACE2 and its potential to be used as a receptor by SARS-CoV-2. We designed a five-category binding score based on the conservation properties of 25 amino acids important for the binding between ACE2 and the SARS-CoV-2 spike protein. Only mammals fell into the medium to very high categories and only catarrhine primates into the very high category, suggesting that they are at high risk for SARS-CoV-2 infection. We employed a protein structural analysis to qualitatively assess whether amino acid changes at variable residues would be likely to disrupt ACE2/SARS-CoV-2 spike protein binding and found the number of predicted unfavorable changes significantly correlated with the binding score. Extending this analysis to human population data, we found only rare (frequency <0.001) variants in 10/25 binding sites. In addition, we found significant signals of selection and accelerated evolution in the ACE2 coding sequence across all mammals, and specific to the bat lineage. Our results, if confirmed by additional experimental data, may lead to the identification of intermediate host species for SARS-CoV-2, guide the selection of animal models of COVID-19, and assist the conservation of animals both in native habitats and in human care.

Broad Host Range of SARS-CoV-2 Predicted by Comparative and Structural Analysis of ACE2 in Vertebrates.

The novel coronavirus SARS-CoV-2 is the cause of Coronavirus Disease-2019 (COVID-19). The main receptor of SARS-CoV-2, angiotensin I converting enzyme 2 (ACE2), is now undergoing extensive scrutiny to understand the routes of transmission and sensitivity in different species. Here, we utilized a unique dataset of 410 vertebrates, including 252 mammals, to study cross-species conservation of ACE2 and its likelihood to function as a SARS-CoV-2 receptor. We designed a five-category ranking score based on the conservation properties of 25 amino acids important for the binding between receptor and virus, classifying all species from very high to very low. Only mammals fell into the medium to very high categories, and only catarrhine primates in the very high category, suggesting that they are at high risk for SARS-CoV-2 infection. We employed a protein structural analysis to qualitatively assess whether amino acid changes at variable residues would be likely to disrupt ACE2/SARS-CoV-2 binding, and found the number of predicted unfavorable changes significantly correlated with the binding score. Extending this analysis to human population data, we found only rare (<0.1%) variants in 10/25 binding sites. In addition, we observed evidence of positive selection in ACE2 in multiple species, including bats. Utilized appropriately, our results may lead to the identification of intermediate host species for SARS-CoV-2, justify the selection of animal models of COVID-19, and assist the conservation of animals both in native habitats and in human care.

BarkBase: Epigenomic Annotation of Canine Genomes.

Dogs are an unparalleled natural model for investigating the genetics of health and disease, particularly for complex diseases like cancer. Comprehensive genomic annotation of regulatory elements active in healthy canine tissues is crucial both for identifying candidate causal variants and for designing functional studies needed to translate genetic associations into disease insight. Currently, canine geneticists rely primarily on annotations of the human or mouse genome that have been remapped to dog, an approach that misses dog-specific features. Here, we describe BarkBase, a canine epigenomic resource available at barkbase.org. BarkBase hosts data for 27 adult tissue types, with biological replicates, and for one sample of up to five tissues sampled at each of four carefully staged embryonic time points. RNA sequencing is complemented with whole genome sequencing and with assay for transposase-accessible chromatin using sequencing (ATAC-seq), which identifies open chromatin regions. By including replicates, we can more confidently discern tissue-specific transcripts and assess differential gene expression between tissues and timepoints. By offering data in easy-to-use file formats, through a visual browser modeled on similar genomic resources for human, BarkBase introduces a powerful new resource to support comparative studies in dogs and humans.

Combining Citizen Science and Genomics to Investigate Tick, Pathogen, and Commensal Microbiome at Single-Tick Resolution.

The prevalence of tickborne diseases worldwide is increasing virtually unchecked due to the lack of effective control strategies. The transmission dynamics of tickborne pathogens are influenced by the tick microbiome, tick co-infection with other pathogens, and environmental features. Understanding this complex system could lead to new strategies for pathogen control, but will require large-scale, high-resolution data. Here, we introduce Project Acari, a citizen science-based project to assay, at single-tick resolution, species, pathogen infection status, microbiome profile, and environmental conditions of tens of thousands of ticks collected from numerous sites across the United States. In the first phase of the project, we collected more than 2,400 ticks wild-caught by citizen scientists and developed high-throughput methods to process and sequence them individually. Applying these methods to 192 Ixodes scapularis ticks collected in a region with a high incidence of Lyme disease, we found that 62% were colonized by Borrelia burgdorferi, the Lyme disease pathogen. In contrast to previous reports, we did not find an association between the microbiome diversity of a tick and its probability of carrying B. burgdorferi. However, we did find undescribed associations between B. burgdorferi carriage and the presence of specific microbial taxa within individual ticks. Our findings underscore the power of coupling citizen science with high-throughput processing to reveal pathogen dynamics. Our approach can be extended for massively parallel screening of individual ticks, offering a powerful tool to elucidate the ecology of tickborne disease and to guide pathogen-control initiatives.

Analysis of the Human Mucosal Response to Cholera Reveals Sustained Activation of Innate Immune Signaling Pathways.

To better understand the innate immune response to Vibrio cholerae infection, we tracked gene expression in the duodenal mucosa of 11 Bangladeshi adults with cholera, using biopsy specimens obtained immediately after rehydration and 30 and 180 days later. We identified differentially expressed genes and performed an analysis to predict differentially regulated pathways and upstream regulators. During acute cholera, there was a broad increase in the expression of genes associated with innate immunity, including activation of the NF-κB, mitogen-activated protein kinase (MAPK), and Toll-like receptor (TLR)-mediated signaling pathways, which, unexpectedly, persisted even 30 days after infection. Focusing on early differences in gene expression, we identified 37 genes that were differentially expressed on days 2 and 30 across the 11 participants. These genes included the endosomal Toll-like receptor gene TLR8, which was expressed in lamina propria cells. Underscoring a potential role for endosomal TLR-mediated signaling in vivo, our pathway analysis found that interferon regulatory factor 7 and beta 1 and alpha 2 interferons were among the top upstream regulators activated during cholera. Among the innate immune effectors, we found that the gene for DUOX2, an NADPH oxidase involved in the maintenance of intestinal homeostasis, was upregulated in intestinal epithelial cells during cholera. Notably, the observed increases in DUOX2 and TLR8 expression were also modeled in vitro when Caco-2 or THP-1 cells, respectively, were stimulated with live V. cholerae but not with heat-killed organisms or cholera toxin alone. These previously unidentified features of the innate immune response to V. cholerae extend our understanding of the mucosal immune signaling pathways and effectors activated in vivo following cholera.

Epigenetic memory via concordant DNA methylation is inversely correlated to developmental potential of mammalian cells.

In storing and transmitting epigenetic information, organisms must balance the need to maintain information about past conditions with the capacity to respond to information in their current and future environments. Some of this information is encoded by DNA methylation, which can be transmitted with variable fidelity from parent to daughter strand. High fidelity confers strong pattern matching between the strands of individual DNA molecules and thus pattern stability over rounds of DNA replication; lower fidelity confers reduced pattern matching, and thus greater flexibility. Here, we present a new conceptual framework, Ratio of Concordance Preference (RCP), that uses double-stranded methylation data to quantify the flexibility and stability of the system that gave rise to a given set of patterns. We find that differentiated mammalian cells operate with high DNA methylation stability, consistent with earlier reports. Stem cells in culture and in embryos, in contrast, operate with reduced, albeit significant, methylation stability. We conclude that preference for concordant DNA methylation is a consistent mode of information transfer, and thus provides epigenetic stability across cell divisions, even in stem cells and those undergoing developmental transitions. Broader application of our RCP framework will permit comparison of epigenetic-information systems across cells, developmental stages, and organisms whose methylation machineries differ substantially or are not yet well understood.

Integrating evolutionary and regulatory information with a multispecies approach implicates genes and pathways in obsessive-compulsive disorder.

Obsessive-compulsive disorder is a severe psychiatric disorder linked to abnormalities in glutamate signaling and the cortico-striatal circuit. We sequenced coding and regulatory elements for 608 genes potentially involved in obsessive-compulsive disorder in human, dog, and mouse. Using a new method that prioritizes likely functional variants, we compared 592 cases to 560 controls and found four strongly associated genes, validated in a larger cohort. NRXN1 and HTR2A are enriched for coding variants altering postsynaptic protein-binding domains. CTTNBP2 (synapse maintenance) and REEP3 (vesicle trafficking) are enriched for regulatory variants, of which at least six (35%) alter transcription factor-DNA binding in neuroblastoma cells. NRXN1 achieves genome-wide significance (p = 6.37 × 10-11) when we include 33,370 population-matched controls. Our findings suggest synaptic adhesion as a key component in compulsive behaviors, and show that targeted sequencing plus functional annotation can identify potentially causative variants, even when genomic data are limited.Obsessive-compulsive disorder (OCD) is a neuropsychiatric disorder with symptoms including intrusive thoughts and time-consuming repetitive behaviors. Here Noh and colleagues identify genes enriched for functional variants associated with increased risk of OCD.

Why do fragile X carrier frequencies differ between Asian and non-Asian populations?

Asian and non-Asian populations have been reported to differ substantially in the distribution of fragile X alleles into the normal (< 55 CGG repeats), premutation (55-199 CGG repeats), and full-mutation (> 199 CGG repeats) size classes. Our statistical analyses of data from published general-population studies confirm that Asian populations have markedly lower frequencies of premutation alleles, reminiscent of earlier findings for expanded alleles at the Huntington's Disease locus. To examine historical and contemporary factors that may have shaped and now sustain allele-frequency differences at the fragile X locus, we develop a population-genetic/epigenetic model, and apply it to these published data. We find that founder-haplotype effects likely contribute to observed frequency differences via substantially lower mutation rates in Asian populations. By contrast, any premutation frequency differences present in founder populations would have disappeared in the several millennia since initial establishment of these groups. Differences in the reproductive fitness of female premutation carriers arising from fragile X primary ovarian insufficiency (FXPOI) and from differences in mean maternal age may also contribute to global variation in carrier frequencies.

Transient exposure to low levels of insecticide affects metabolic networks of honeybee larvae.

The survival of a species depends on its capacity to adjust to changing environmental conditions, and new stressors. Such new, anthropogenic stressors include the neonicotinoid class of crop-protecting agents, which have been implicated in the population declines of pollinating insects, including honeybees (Apis mellifera). The low-dose effects of these compounds on larval development and physiological responses have remained largely unknown. Over a period of 15 days, we provided syrup tainted with low levels (2 µg/L(-1)) of the neonicotinoid insecticide imidacloprid to beehives located in the field. We measured transcript levels by RNA sequencing and established lipid profiles using liquid chromatography coupled with mass spectrometry from worker-bee larvae of imidacloprid-exposed (IE) and unexposed, control (C) hives. Within a catalogue of 300 differentially expressed transcripts in larvae from IE hives, we detect significant enrichment of genes functioning in lipid-carbohydrate-mitochondrial metabolic networks. Myc-involved transcriptional response to exposure of this neonicotinoid is indicated by overrepresentation of E-box elements in the promoter regions of genes with altered expression. RNA levels for a cluster of genes encoding detoxifying P450 enzymes are elevated, with coordinated downregulation of genes in glycolytic and sugar-metabolising pathways. Expression of the environmentally responsive Hsp90 gene is also reduced, suggesting diminished buffering and stability of the developmental program. The multifaceted, physiological response described here may be of importance to our general understanding of pollinator health. Muscles, for instance, work at high glycolytic rates and flight performance could be impacted should low levels of this evolutionarily novel stressor likewise induce downregulation of energy metabolising genes in adult pollinators.

Statistical inference of in vivo properties of human DNA methyltransferases from double-stranded methylation patterns.

DNA methyltransferases establish methylation patterns in cells and transmit these patterns over cell generations, thereby influencing each cell's epigenetic states. Three primary DNA methyltransferases have been identified in mammals: DNMT1, DNMT3A and DNMT3B. Extensive in vitro studies have investigated key properties of these enzymes, namely their substrate specificity and processivity. Here we study these properties in vivo, by applying novel statistical analysis methods to double-stranded DNA methylation patterns collected using hairpin-bisulfite PCR. Our analysis fits a novel Hidden Markov Model (HMM) to the observed data, allowing for potential bisulfite conversion errors, and yields statistical estimates of parameters that quantify enzyme processivity and substrate specificity. We apply this model to methylation patterns established in vivo at three loci in humans: two densely methylated inactive X (Xi)-linked loci (FMR1 and G6PD), and an autosomal locus (LEP), where methylation densities are tissue-specific but moderate. We find strong evidence for a high level of processivity of DNMT1 at FMR1 and G6PD, with the mean association tract length being a few hundred base pairs. Regardless of tissue types, methylation patterns at LEP are dominated by DNMT1 maintenance events, similar to the two Xi-linked loci, but are insufficiently informative regarding processivity to draw any conclusions about processivity at that locus. At all three loci we find that DNMT1 shows a strong preference for adding methyl groups to hemi-methylated CpG sites over unmethylated sites. The data at all three loci also suggest low (possibly 0) association of the de novo methyltransferases, the DNMT3s, and are consequently uninformative about processivity or preference of these enzymes. We also extend our HMM to reanalyze published data on mouse DNMT1 activities in vitro. The results suggest shorter association tracts (and hence weaker processivity), and much longer non-association tracts than human DNMT1 in vivo.